Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
5,202
datasets available to search
ShareScore release 0.7.1
Dataset results
5,202 results for “Insects”
Data and code from: Insect biomass decline scaled to species diversity: General patterns derived from a hoverfly community
<p>To study changes in flying insect communities, and hoverflies in particular, malaise trap samples from a German site were compared between two years (Hallmann et al. 2020). The data files deposited here contain data obtained from six malaise traps in the Wahnbachtal (North Rhine-Westphalia, Germany, 50.851944N, 7.320833E) that were deployed in 1989 and again in 2014, at the exact same locations. Traps were situated in wet meadows as well as tall perennial meadows, in close proximity to shrub corridors, to forest–grassland borders, and to the Wahnbach River and surrounded by agricultural land, essentially a rather heterogeneous habitat. The Wahnbach River and the greater part of the valley are protected for watershed purposes and are subject to nature conservation management by the Wahnbach Talperrenverband. Hence, several restrictions apply to safeguard against water contamination.</p> <p>Total insect biomass collected with these traps was already included in Hallmann et al. (2017), but here we focus on additional information: the abundance and richness of hoverflies (Syrphidae) in each of the collected samples (pots). Methodologies of collection are described in Sorg (1990), Schwan et al. (1993), Sorg et al. (2013), Hallmann et al. (2017), and Ssymank et al. (2018). In brief, malaise traps were deployed throughout the growing season and operated continuously (day and night). Malaise trap construction (e.g., size, material, colouring, and ground sealing) and placing (e.g., positioning, orientation, and slope of the locations) were standardised in all aspects. Insect samples were preserved in 80% ethanol solution. Catches of the six traps investigated in the present study were emptied regularly: On average exposure intervals were 7.0 d (SD = 0.5) in 1989 and 16.7 d (SD = 5.6) in 2014. Across the six traps in 2014 the total exposure time (in number of days) was 42% higher compared to 1989. All collected samples (n = 196) were used in the present analysis with in total 19,604 individual hoverflies counted, distributed over 162 species and 59 genera.</p> <p>To assess how environmental conditions have changed over the 25 year, several additional datasets were assembled. Climatic<br> data were obtained from 169 climatic stations and were used to interpolate daily weather variables to each trap location, using spatiotemporal kriging. These steps are described in detail in Hallmann et al. (2017).</p> <p>Our analysis (see R code) consists of three components. First, we considered total abundance, species richness, and species diversity, at two temporal scales: pooled per year, i.e., across the sampling season, and seasonally (i.e., per day), and we compared these metrics between 1989 and 2014. Second, we examined how total flying biomass (i.e., the weight of all trapped insects, of which hoverflies are only a small proportion) related to total abundance as well as species richness of hoverflies. Third, we derived persistence probabilities and population growth rate trends per species, to examine interspecific variation in these parameters.</p> <p>Descriptions of the deposited files:</p> <p><strong>Groups.csv</strong><br> MF_NR = identifier of each of the six malaise trap locations<br> yrf = year of sampling<br> pot = sample identifier<br> dt = number of sampling days<br> from.dnr = day-of-the-year on which a pot was attached to a malaise trap<br> to.dnr = day-of-the-year on which a pot was collected from a malaise trap<br> mean.daynr = mean day-of-the-year of the sampling period<br> Nspec = number of different hoverfly species found in a pot<br> Nind = number of hoverfly individuals found in a pot</p> <p><strong>Counts.csv</strong><br> A matrix of counts of individual hoverflies per pot per species. The 196 rows represent the pots in the same order as in the file 'Groups.csv'. The columns represent the 162 different hoverfly species found. The scientific species names are indicated in the column headers.</p> <p><strong>PairedData.csv</strong><br> pot = sample identifier<br> JAHR = year of sampling<br> MF_NR = identifier of each of the six malaise trap locations<br> dt = number of sampling days<br> from.dnr = day-of-the-year on which a pot was attached to a malaise trap<br> to.dnr = day-of-the-year on which a pot was collected from a malaise trap<br> NI = number of hoverfly individuals found in a potbiomass.daily<br> NSP = number of different hoverfly species found in a pot<br> biomass.daily = daily fresh weight [gram] of flying insects: total fresh weight in a pot divided by the number of sampling days.</p> <p><strong>ModelFrame.csv</strong><br> MF_NR = identifier of each of the six malaise trap locations<br> yrf = year of sampling<br> pot = sample identifier<br> dt = number of sampling days<br> from.dnr = day-of-the-year on which a pot was attached to a malaise trap<br> to.dnr = day-of-the-year on which a pot was collected from a malaise trap<br> mean.daynr = mean day-of-the-year of the sampling period<br> plot = identifier of each of the six malaise trap locations<br> date = date for which the weather variables are interpolated<br> daynr = day-of-the-year for which the weather variables are interpolated<br> altitude = altitude [m] of the malaise trap locations<br> year = year of sampling<br> temperature = interpolated temperature [degrees Celsius]<br> precipitation = interpolated precipitation [mm per day]<br> wind.speed = interpolated wind speed [m/s]</p> <p><strong>Data_Rcode.pdf</strong><br> This pdf provides the R-code behind the analysis of the Hoverfly data. Three datasets are provided along with this R-code document, namely "Counts.csv", "Groups.csv", "PairedData.csv" and "ModelFrame.csv". Additionally, the BUGS-code ""syrphidModel.jag" is required for running the daily-activity model in JAGS.</p> <p><strong>syrphidModel.jag</strong><br> This BUGS-code is required for running the daily-activity model in JAGS.</p>
Nutritional value of edible insects: special emphasis on their micro and macro nutrients
<p>The data set was prepared by collecting the existed information regarding the nutritional value of insects from relevant published papers. For each column, variables or descriptors were expressed in the same unit. The information from each insect in a raw were followed by a reference of the paper which the information is taken from with the DOI which makes it easily accessible for the readers.</p>
Supplementary data for "The subgenual organ complex in stick insects: Functional morphology and mechanical coupling of a complex mechanosensory organ"
<p>µCT-scans of the upper tibial regions of the foreleg (T1) and the midleg (T2) of <em>Ramulus artemis</em> (Westwood, 1859), <em>Carausius morosus</em> (Sinéty, 1901), and <em>Sipyloidea sipylus</em> (Westwood, 1859). For use of scans, please cite the following publication:</p> <p>Strauß, J., Moritz, L. & Rühr, P.T. (<strong>2021</strong>): The subgenual organ complex in stick insects: Functional morphology and mechanical coupling of a complex mechanosensory organ. <em>Frontiers in Ecology and Evolution (Research Topic “Evolutionary Biomechanics of Sound Production and Reception”)</em>. doi: <a href="https://doi.org/10.3389/fevo.2021.632493">10.3389/fevo.2021.632493</a>.</p> <p>All scans were performed with a commercial μCT desktop system (Skyscan 1272, Bruker microCT, Kontich, Belgium) at the Zoological Research Museum Alexander Koenig, Leibniz Institute for Animal Biodiversity, Bonn, Germany.</p> <p><strong>µCT scan settings of all samples:</strong></p> <p><em>Ramulus artemis:</em></p> <ul> <li>tube voltage = 30 kV</li> <li>ube current = 200 μA</li> <li>target = tungsten</li> <li>no filter</li> <li>total sample rotation = 360°</li> <li>angular step size = 0.2°</li> <li>exposure time = 1980 ms</li> <li>binning = 1x1</li> <li>averaging = 8</li> <li>random movement = 15 px</li> <li>voxel size = 1.8 μm</li> <li>fixation: Bouin's solution (24 hours)</li> <li>staining: 0.3% PTA (21 days)</li> <li>storage: 70% EtOH</li> <li>surrounding medium in scan: 70% EtOH</li> <li>filenames: Ramulus_artemis_T1.tif; Ramulus_artemis_T2.tif</li> </ul> <p><em>Carausius morosus:</em></p> <ul> <li>tube voltage = 29 kV</li> <li>ube current = 200 μA</li> <li>target = tungsten</li> <li>no filter</li> <li>total sample rotation = 360°</li> <li>angular step size = 0.2°</li> <li>exposure time = 1900 ms</li> <li>binning = 1x1</li> <li>averaging = 5</li> <li>random movement = 15 px</li> <li>voxel size = 1.0 μm</li> <li>fixation: Bouin's solution (24 hours)</li> <li>staining: 0.3% PTA (21 days)</li> <li>storage: 70% EtOH</li> <li>surrounding medium in scan: 70% EtOH</li> <li>filenames: Carausius_morosus_T1.tif; Carausius_morosus_T2.tif</li> </ul> <p><em>Sipyloidea sipylus:</em></p> <ul> <li>tube voltage = 29 kV</li> <li>ube current = 200 μA</li> <li>target = tungsten</li> <li>no filter</li> <li>total sample rotation = 360°</li> <li>angular step size = 0.2°</li> <li>exposure time = 1900 ms</li> <li>binning = 1x1</li> <li>averaging = 7</li> <li>random movement = 15 px</li> <li>voxel size = 1.8 μm</li> <li>fixation: Bouin's solution (24 hours)</li> <li>staining: 0.3% PTA (21 days)</li> <li>storage: 70% EtOH</li> <li>surrounding medium in scan: 70% EtOH</li> <li>filenames: Sipyloidea_sipylus_T1.tif; Sipyloidea_sipylus_T2.tif</li> </ul>
Can the botanical azadirachtin replace phased-out soil insecticides in suppressing the soil insect pest Diabrotica virgifera virgifera ?
<p><strong>Can the botanical <em>azadirachtin</em> replace phased-out soil insecticides in suppressing the soil insect pest <em>Diabrotica virgifera virgifera </em>?</strong></p> <p><strong>Background</strong></p> <p>Due to recent bans on the use of several soil insecticides and insecticidal seed coatings, soil-dwelling insect pests are increasingly difficult to manage. One example is the western corn rootworm (<em>Diabrotica virgifera virgifera</em>, Coleoptera: Chrysomelidae), a serious root-feeder of maize (<em>Zea mays</em>). We investigated whether the less problematic botanical <em>azadirachtin</em>, widely used against above-ground insects, could become an option for the control of this soil insect pest.</p> <p><strong>Methods</strong></p> <p>Artificial diet-based bioassays were implemented under standard laboratory conditions to establish lethal dose curves for the pest larvae. Then, potted-plant experiments were implemented in greenhouse to assess feasibility and efficacy of a novel granular formulation of <em>azadirachtin </em>under more natural conditions and in relation to standard insecticides.</p> <p><strong>Results</strong></p> <p>Bioassays in three repetitions revealed a 3-day LD<sub>50</sub> of 22.3 µg <em>azadirachtin</em> per ml which corresponded to 0.45 µg per neonate of <em>D. v. virgifera </em>and a 5-day LD<sub>50</sub> of 19.3 µg per ml or 0.39 µg per first to second instar larva. No sublethal effects were observed. The three greenhouse experiments revealed that the currently proposed standard dose of a granular formulation of 38 g<em> azadirachtin </em>per hectare for in-furrow application at sowing is not enough to control <em>D. v. virgifera </em>or to prevent root damage. At 10x standard-dose total pest control was achieved as well as the prevention of most root damage. This was better than the efficacy achieved by <em>cypermethrin</em>-based granules and comparable to <em>tefluthrin</em>- granules, or <em>thiamethoxam</em> seed coatings. The ED<sub>50</sub> for suppressing larval populations were estimated at 92 g <em>azadirachtin</em> per ha, for preventing heavy root damage 52 g /ha and for preventing general root damage 220 g /ha.</p> <p><strong>Conclusions</strong></p> <p>There seems clear potential for the development of neem-based botanical soil insecticides for arable crops such as maize. They might become, if doses are increased and more soil insecticides phased out, a promising, safer solution as part of the integrated pest management toolkit against soil insects.</p>
Supplementary materials for: How effective are insect aposematism and Batesian mimicry in deterring a wild avian predator?
<p><strong><a name="_Hlk180513890"></a>Acoustic_parameters_10cm.txt</strong><br>Acoustic parameters of the sounds produced by insects in flight, species recorded at 10 cm from the microphone.</p> <p><strong>Acoustic_parameters_5cm.txt<br></strong>Acoustic parameters of the sounds produced by insects in flight, species recorded at 5 cm from the microphone.</p> <p><strong>Robin_behaviours.txt</strong> <br><em>Erithacus rubecula</em> reactions measured in Boris software from videos of behavioural experiments.</p> <p><strong>Rscript_robin_behaviours.R</strong><br>R script used for the analysis of robins’ behaviours (using Robin_behaviours.txt).</p> <p><strong>Rscript_acoustical_analyses.R</strong><br>R script used for the analysis of acoustical parameters of insect buzzing sounds (using Acoustic_parameters_10cm.txt and Acoustic_parameters_5cm.txt).</p> <p><strong>Robin_experiment_video.mp4<br></strong>Behavioural experiment with a wild European robin (<em>Erithacus rubecula</em>) in its habitat. A freshly defrosted insect specimen and the corresponding buzzing sound of each recorded hymenopteran model and lepidopteran mimic (plus a housefly as a control) were presented in random order to the robin at a feeder with <em>Tenebrio molitor</em> larvae.</p> <p><strong>Robin_experiment_video_Metadata.docx</strong><br><span>Metadata for the supplementary video Robin_experiment_video.mp4.</span></p>
Data from: Synergistic effects of grass competition and insect herbivory on the weed Rumex obtusifolius in an inundative biocontrol approach
<p>Data are from a field experiment to test for synergistic interactions between grass competition and herbivory on <i>Rumex obtusifolius</i>, a prominent weed in temperate grasslands worldwide.</p><p><i>Rumex obtusifolius</i> was grown in the presence and absence of competition from the grass <i>Lolium perenne</i> and subjected to herbivory through targeted inoculation with root-boring <i>Pyropteron</i> spp.</p><p>To explore whether the interactive effects of competition and herbivory were size-dependent, <i>R. obtusifolius</i> was planted covering a large range of plant sizes found in managed grasslands.</p><p>The experimental layout followed a split-split plot design. Main-level factor was <i>L. perenne</i> competition, split-level factor was herbivory application, split-split-level factor was initial root mass of <i>R. obtusifolius</i>. Main-plots were arranged according to a randomized complete block design on the site (8 blocks, each containing a <i>L. perenne</i> competition and a no competition treatment).</p>
Data and code for: Insect herbivores drive sex allocation in angiosperm flowers
<p><strong>Code and Data for the paper:</strong></p> <p>Insect herbivores drive sex allocation in angiosperm flowers</p> <p><em>Carlos Roberto Fonseca, Martin M. Gossner, Johannes Kollmann, Martin Brändle, Gustavo Brant Paterno</em></p> <p> </p> <p>Content of the repository</p> <ol> <li> <p><strong>Data</strong>: the folder <code>data</code> contains all data required to reproduce analyses, figures and tables.</p> </li> <li> <p><strong>Outputs</strong>: the folder <code>output</code> contains the figures, tables and temporary files generated.</p> </li> <li> <p><strong>Code</strong>: the folder <code>scripts</code> contains all scripts (.R) that generated results, figures and tables used in the manuscript and in the supporting information.</p> </li> <li> <p><strong>Supplementary information</strong>: the folder <code>doc</code> contains the supplementary information associated to the paper.</p> </li> </ol>
Supplementary material for "Patterns of high-flying insect abundance are shaped by landscape type and abiotic conditions"
<p><strong>Abstract</strong></p> <p>Insects are of increasing conservation concern as a severe decline of both biomass and biodiversity have been reported. At the same time, data on where and when they occur in the airspace is still sparse, and we currently do not know whether their density is linked to the type of landscape above which they occur. Here, we combine data of high-flying insect abundance from six locations across Switzerland representing rural, urban and mountainous landscapes, which was recorded using vertical-looking radar devices. We analysed the abundance of high-flying insects in relation to meteorological factors, daytime, and type of landscape. Air pressure was positively related to insect abundance, wind speed showed an optimum, and temperature and wind direction did not show a clear relationship. Mountainous landscapes showed a higher insect abundance than the other two landscape types. Insect abundance increased in the morning, decreased in the afternoon, had a peak after sunset, and then declined again, though the extent of this general pattern slightly differed between landscape types. We conclude that the abundance of high-flying insects is not only related to abiotic parameters, but also to the type of landscapes. Thus, conservation measures implemented on the ground should start to also account for the needs of high-flying insects.</p>
InsectSet32: Dataset for automatic acoustic identification of insects (Orthoptera and Cicadidae)
<p>This dataset contains recordings of 32 sound producing insect species with a total 335 files and a length of 57 minutes. The dataset was compiled for training neural networks to automatically identify insect species while comparing adaptive, waveform-based frontends to conventional mel-spectrogram frontends for audio feature extraction. This work was <a href="https://doi.org/10.1371/journal.pcbi.1011541">published</a> in PLOS Computational Biology and this dataset can be used to replicate the results, as well as other uses. The scripts for audio processing and the machine learning implementations are published on <a href="https://github.com/mariusfaiss/InsectSet32-Adaptive-Representations-of-Sound-for-Automatic-Insect-Recognition">Github</a>.</p> <p>The recordings are split into two datasets. Roughly half of the recordings (147) are of nine species belonging to the order Orthoptera. These recordings stem from a dataset that was originally compiled by <a href="https://orcid.org/0000-0002-8929-2737">Baudewijn Odé</a> (unpublished). </p> <p>The remaining recordings (188) are of 23 species in the family Cicadidae. These recordings were selected from the Global Cicada Sound Collection hosted on <a href="https://bio.acousti.ca/">Bioacoustica</a> (<a href="https://doi.org/10.1093/database/bav054">doi.org/10.1093/database/bav054</a>), including recordings published in <a href="https://doi.org/10.3897/BDJ.3.e5792">doi.org/10.3897/BDJ.3.e5792</a> & <a href="https://doi.org/10.11646/zootaxa.4340.1">doi.org/10.11646/zootaxa.4340.1</a>. Many recordings from this collection included speech annotations in the beginning of the recordings, therefore the last ten seconds of audio were extracted and used in this dataset. </p> <p>All files were manually inspected and files with strong noise interference or with sounds of multiple species were removed. Between species, the number of files ranges from four to 22 files and the length from 40 seconds to almost nine minutes of audio material for a single species. The files range in length from less than one second to several minutes. All original files were available with sample rates of at least 44.1 kHz or higher but were resampled to 44.1 kHz mono WAV files for consistency. The annotation files contain information for each recording, including the file name, species name and identifier, as well as the data subset they were included in for training the neural network (training, test, validation).</p>
Code/data to accompany publication "Using cloud radar to investigate the effect of rainfall on migratory insect flight"
<p>Code/data to accompany publication "Using cloud radar to investigate the effect of rainfall on migratory insect flight". The cloud radar data files contains all the data used in the publication "Using cloud radar to investigate the effect of rainfall on migratory insect flight" by Charlotte E. Wainwright, Sabrina N. Volponi, Phillip M. Stepanian, Don R. Reynolds, and David H. Richter, published in Methods in Ecology and Evolution in 2022. The MATLAB code implements the method described in the paper on the data files included.</p>
Dataset Natural plant disease suppressiveness in soils extends to insect pest control
<p>This dataset is related to the study "<strong>Natural plant disease suppressiveness in soils extends to insect pest control</strong>" (Harmsen et al., 2024) and contains the raw data described therein. </p> <p>Sequencing data used in this study has been deposited in the NCBI Sequence Read Archive under the BioProject number <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1075215/">PRJNA1075215</a>.</p> <p>The scripts used to analyze the data generated in the study are available at <a href="https://github.com/nhrmsn/SuppressSoil-Data">GitHub</a>. </p>
Data for: Crall et al., Spatial fidelity of workers predicts collective response to disturbance in a social insect
<p>Dataset for: Crall et al., Spatial fidelity of workers predicts collective response to disturbance in a social insect, in final revision for Nature Communications.</p> <p>Includes two files - one behavioral data from uniquely identified worker bumblebees, and the second containing metadata for the colonies from which these data were generated (including experimental treatments, locations, sizes, etc.).</p>
Trophic metacommunities in bromeliad-dwelling insects
<p>This data was collected by D. S. Srivastava and members of her research lab (including B. Gilbert, K. Kirby, J. Ngai, J. Petermann, B. Starzomski) at Estación Biológica Pitilla, in the Área de Conservación Guanacaste in north-western Costa Rica in 1997, 2000, 2002, 2004, 2010. Over these five years, we collected a total of 85 bromeliads between late September and early December. Specifically, this data relates to the abundance of the mosquitoes in the genus Wyeomyia and Culex, and their predator Mecistogaster modesta.</p> <p>Water depths were measured to the nearest mm in three marked leaves of 30 bromeliads, every two days for one year (8 October 2012 to 9 October 2013). The maximum volume of each bromeliad was measured at the inception of the survey. We assumed that mosquito larvae encountered in our invertebrate survey could be affected by water depths only from the period 15 September to 22 December, that is, at most three weeks before and after our survey (as a mosquito encountered at the beginning of the invertebrate survey may be already a late instar, and at the end of our invertebrate survey may be just an early instar). We trimmed our year of water level data to this 15 September-22 December period, and calculated the proportion of days each of the 30 bromeliads had standing water (defined as >5mm moisture, as the basal debris retains some moisture in the absence of standing water).</p>
Insect Development
<p>Data on the <a href="http://eol.org/schema/terms/DevelopmentalMode">developmental modes</a> of insects derived from the following sources:</p> <p>Belles, Xavier. 2011. Origin and Evolution of Insect Metamorphosis. In: Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester. <a href="https://doi.org/10.1002/9780470015902.a0022854">https://doi.org/10.1002/9780470015902.a0022854</a></p> <p>Štys, P. and Šobotník, J., 1999. Comments on classifications of insect ontogenies, and occurrence of proneometabolous wing development in termite genus Prorhinotermes (Hexapoda: Isoptera). Acta Soc. Zool. Bohem, 63, pp.483-492.</p> <p>Truman, J.W., 2019. The evolution of insect metamorphosis. Current Biology, 29(23), pp.R1252-R1268. <a href="https://doi.org/10.1016/j.cub.2019.10.009">https://doi.org/10.1016/j.cub.2019.10.009 </a></p> <p>Vea, I. M. and Minakuchi, C. 2021. Atypical insects: molecular mechanisms of unusual life history strategies. Current Opinion in Insect Science 43:46-53. <a href="https://doi.org/10.1016/j.cois.2020.09.016">https://doi.org/10.1016/j.cois.2020.09.016</a></p>
Insect Pain Database: Sting Pain review
First hand reports by biologists of relative intensity of pain for bites and stings of various fauna, literature sources.
Insect Wings
<p>Data on insect wing morphology derived from the following sources: </p> <p>Andersen, N., Cheng, L. 2004. The marine insect Halobates (Heteroptera: Gerridae): Biology, adaptations, distribution, and phylogeny. Oceanography and Marine Biology: An Annual Review 42:119–180. <a href="https://doi.org/10.1201/9780203507810.ch5">https://doi.org/10.1201/9780203507810.ch5</a></p> <p>Ball, E. D. and Hartzell A. 1922. Review of the Desert Leafhoppers of the Orgerini (Rhynchota Fulgoridae). Annals of the Entomological Society of America 15(2):137-152. <a href="https://doi.org/10.1093/aesa/15.2.137">https://doi.org/10.1093/aesa/15.2.137</a></p> <p>Bickel, D. J. 2006. Papallacta (Diptera: Dolichopodidae), a New Stenopterous Genus from the Páramo of Ecuador. Tijdschrift Voor Entomologie 149(2):209–13. <a href="https://doi.org/10.1163/22119434-900000201">https://doi.org/10.1163/22119434-900000201</a>.</p> <p>Braendle, C., Davis, G., Brisson, J. et al. 2006. Wing dimorphism in aphids. Heredity 97:192-199. <a href="https://doi.org/10.1038/sj.hdy.6800863">https://doi.org/10.1038/sj.hdy.6800863</a></p> <p>Brothers, D.J., Lelej, A.S. 2017. Phylogeny and higher classification of Mutillidae (Hymenoptera) based on morphological reanalyses. Journal of Hymenoptera Research 60:1–97. <a href="https://doi.org/10.3897/jhr.60.20091">https://doi.org/10.3897/jhr.60.20091</a></p> <p>Byers, G.V. 1969. Evolution of Wing Reduction in Crane Flies (diptera: Tipulidae). Evolution 23:346–354. <a href="https://doi.org/10.1111/j.1558-5646.1969.tb03517">https://doi.org/10.1111/j.1558-5646.1969.tb03517</a></p> <p>Byers, G.W. 1997. Biology of Brachypanorpa (Mecoptera: Panorpodidae). Journal of the Kansas Entomological Society 70:313–322. </p> <p>Cambra T, R.A., A, D.Q. 2007. Chilemutilla, a new genus of Mutillidae (Hymenoptera) from Chile, and the description of the first wingless mutillid male from South America. Transactions of the American Entomological Society 133:167–180. <a href="https://doi.org/10.3157/0002-8320(2007)133[167:CANGOM]2.0.CO;2">https://doi.org/10.3157/0002-8320(2007)133[167:CANGOM]2.0.CO;2</a></p> <p>Chen X, Mirab-balou M, Minaei K. 2013. An illustrated key to the genera of Thripinae (Thysanoptera, Thripidae) from Iran. ZooKeys 317: 27-52. <a href="https://doi.org/10.3897/zookeys.317.5447">https://doi.org/10.3897/zookeys.317.5447</a></p> <p>Cheng, L. 1977. The elusive sea bug Hermatobates (Heteroptera). The Pan-Pacific entomologist 53(2):87--97. </p> <p>Davis, D.R., Quintero, D.A., Cambra, R.A. and Aiello, A. 2008. Biology of a new Panamanian bagworm moth (Lepidoptera: Psychidae) with predatory larvae, and eggs individually wrapped in setal cases. Annals of the Entomological Society of America, 101(4):689-702. </p> <p>De Jong, H. and Ciliberti, P. 2014. How cold‐adapted flightless flies dispersed over the northern hemisphere: phylogeny and biogeography of the snow fly genus Chionea D alman (D iptera: Limoniidae). Systematic Entomology, 39(3):563-589. </p> <p>Gnezdilov, Vladimir M. 2012. A New Stenopterous Genus of the Tribe Gaetuliini Fennah (Hemiptera, Fulgoroidea, Tropiduchidae) from Southern Africa - Particular Intercontinental Convergence. AFRICAN INVERTEBRATES 53:8. </p> <p>Grimaldi, D. & Engel, M.S. 2005. Evolution of the Insects. Cambridge University Press. Grimaldi, D. and Underwood, B.A., 1986. Megabraula, a new genus for two new species of Braulidae (Diptera), and a discussion of braulid evolution. Systematic entomology, 11(4):427-438. </p> <p>Hackman, W. 1966. On wing reduction and loss of wings in Lepidoptera.Notulae Entomologica 46:1–16. Heppner, J.B., 1991. Brachyptery and aptery in Lepidoptera. Tropical Lepidoptera Research 2:11-40. </p> <p>Hölldobler, B. & Wilson, E. O. 1990. The Ants. Harvard University Press. Hopkins H. 2014. A revision of the genus Arenivaga (Rehn) (Blattodea, Corydiidae), with descriptions of new species and key to the males of the genus. ZooKeys 384:1-256. <a href="https://doi.org/10.3897/zookeys.384.6197">https://doi.org/10.3897/zookeys.384.6197</a></p> <p>Lambdin P. 2008. Scale Insects and Mealybugs (Hemiptera: Coccoidea). In: Capinera J.L. (eds) Encyclopedia of Entomology. Springer, Dordrecht. <a href="https://doi.org/10.1007/978-1-4020-6359-6_4040">https://doi.org/10.1007/978-1-4020-6359-6_4040</a></p> <p>Lelej, A.S. and Krombein, K.V. 2001. Review of the Oriental mutillid wasps of the subfamily Ticoplinae (Hymenoptera, Mutillidae). Far Eastern Entomologist 99:1-18. </p> <p>Lloyd, J. E. 2002. 17 - Louse Flies, Keds, and Related Flies (Hippoboscoidea). Pages 349-362 in Medical and Veterinary Entomology, Gary Mullen & Lance Durden, eds., Academic Press. <a href="https://doi.org/10.1016/B978-012510451-7/50019-0">https://doi.org/10.1016/B978-012510451-7/50019-0</a></p> <p>McCulloch GA, Waters JM. Does wing reduction influence the relationship between altitude and insect body size? A case study using New Zealand__s diverse stonefly fauna. Ecology and Evolution. 2018 Jan;8(2):953-960. <a href="https://doi.org/10.1002/ece3.3713">https://doi.org/10.1002/ece3.3713</a></p> <p>Miller, Kelly B., Cheryl Hayashi, Michael F. Whiting, Gavin J. Svenson, and Janice S. Edgerly. 2012. The Phylogeny and Classification of Embioptera (Insecta). Systematic Entomology 37(3):550–70. <a href="https://doi.org/10.1111/j.1365-3113.2012.00628.x">https://doi.org/10.1111/j.1365-3113.2012.00628.x</a></p> <p>Mound L, Nakahara S, Tsuda DM. 2016. Thysanoptera-Terebrantia of the Hawaiian Islands: an identification manual. ZooKeys 549: 71-126. <a href="https://doi.org/10.3897/zookeys.549.6889">https://doi.org/10.3897/zookeys.549.6889</a></p> <p>Mound, L. & Moritz, G. 2000. Corroboreethrips, a new genus of minute apterous thrips (Insecta : Thysanoptera : Phlaeothripinae) from the bark of Australian Acacia trees. Invertebrate Taxonomy 14:709-716. <a href="https://doi.org/10.1071/IT00002">https://doi.org/10.1071/IT00002</a></p> <p>Mound, L.A. 2005. THYSANOPTERA: Diversity and Interactions. Annu. Rev. Entomol. 50, 247–269. <a href="https://doi.org/10.1146/annurev.ento.49.061802.123318">https://doi.org/10.1146/annurev.ento.49.061802.123318</a></p> <p>Nadel, H. 2008. Agaonidae (Hymenoptera). In: Capinera J.L. (eds) Encyclopedia of Entomology. Springer, Dordrecht. <a href="https://doi.org/10.1007/978-1-4020-6359-6_104">https://doi.org/10.1007/978-1-4020-6359-6_104</a></p> <p>Nakata, S. & Maa, T.C., 1974. A review of the parasitic earwigs (Dermaptera: Arixeniina; Hemimerina). Pacific Insects 16:307-374. </p> <p>Niitsu, S., Sugawara, H., Hayashi, F. 2017. Evolution of female-specific wingless forms in bagworm moths: Wing reduction in bagworm moths. Evolution & Development 19:9–16. <a href="https://doi.org/10.1111/ede.12213">https://doi.org/10.1111/ede.12213</a></p> <p>O__Brien L.B. 2008. Planthoppers (Hemiptera: Fulgoroidea). In: Capinera J.L. (eds) Encyclopedia of Entomology. Springer, Dordrecht. <a href="https://doi.org/10.1007/978-1-4020-6359-6_2987">https://doi.org/10.1007/978-1-4020-6359-6_2987</a></p> <p>Oswald, J. D. 1996. A New brachypterous Nusalala species from Costa Rica, with comments on the evolution of flightlessness in brown lacewings (Neuroptera: Hemerobiidae). Systematic Entomology 21(4):343–52. <a href="https://doi.org/10.1111/j.1365-3113.1996.tb00603.x">https://doi.org/10.1111/j.1365-3113.1996.tb00603.x</a></p> <p>Peck, S.B. 2006. Distribution and biology of the ectoparasitic beaver beetle Platypsyllus castoris Ritsema in North America (Coleoptera: Leiodidae: Platypsyllinae). Insecta Mundi 20:85–94. Penny, N.D. 1975. Evolution of the Extant Mecoptera. Journal of the Kansas Entomological Society 48:331–350. </p> <p>Pitkin, L.M. and Sattler, K. 1991. Sattleria: a European genus of brachypterous alpine moths (Lepidoptera: Gelechiidae). Bulletin of the British Museum, Natural History. Entomology 60(2):205-241. </p> <p>Rindge, F. H. 1974. A revision of the moth genus Animomyia (Lepidoptera, Geometridae). American Museum novitates 2554:1-23. </p> <p>Roff, Derek A. 1990. The Evolution of Flightlessness in Insects. Ecological Monographs 60(4):389–421. <a href="https://doi.org/10.2307/1943013">https://doi.org/10.2307/1943013</a></p> <p>Roza, André Silva, & Mermudes, José Ricardo Miras. (2020). A new genus of railroad-worm beetles from the Atlantic Rainforest from Brazil (Coleoptera: Phengodidae, Mastinocerinae). Papéis Avulsos de Zoologia, 60(spe), e202060(s.i.).10. Epub May 18, 2020. <a href="https://doi.org/10.11606/1807-0205/2020.60.special-issue.10">https://doi.org/10.11606/1807-0205/2020.60.special-issue.10</a></p> <p>Schuh, R. T. & Slater, J. A. 1995. The True Bugs of the World (Hemiptera: Heteroptera). Classification and Natural History. Cornell University Press, Ithaca, New York. Shovkoon, D.F., 2008. On the rediscovery of Ethmia discrepitella (Rebel, 1901) with remarks on brachyptery in females of Ethmia (Ethmiidae). Nota lepidopterologica 31(2):215–221. </p> <p>Song, H., Béthoux, O., Shin, S. et al. 2020. Phylogenomic analysis sheds light on the evolutionary pathways towards acoustic communication in Orthoptera. Nat Commun 11, 4939. <a href="https://doi.org/10.1038/s41467-020-18739-4">https://doi.org/10.1038/s41467-020-18739-4</a></p> <p>Vickery, V. R. and Sandoval, C. P. 2001. Descriptions of Three New Species of Timema (Phasmatoptera: Timematodea: Timematidae) and Notes on Three Other Species. Journal of Orthoptera Research 10(1):53-61. <a href="https://www.jstor.org/stable/3503674">https://www.jstor.org/stable/3503674 </a></p> <p>Wu C, Liu C-X. 2020. New record of Didymocorypha Wood-Mason (Mantodea, Eremiaphilidae) from China, with description of a new high-altitude wingless mantis species in Asia. ZooKeys 922:51-64. <a href="https://doi.org/10.3897/zookeys.922.47987">https://doi.org/10.3897/zookeys.922.47987</a></p> <p>Yoshizawa, K. and Lienhard, C. 2010. In search of the sister group of the true lice: A systematic review of booklice and their relatives, with an updated checklist of Liposcelididae (Insecta: Psocodea). Arthropod Systematics & Phylogeny, 68(2):181-195.</p>
Spreadsheet template for Body Size Data for North American Orthopteroid Insects
<p>Body size data for orthopteroid insects extracted from:</p> <p>Vickery, V.R., Kevan, D.K.McE., 1985. The insects and arachnids of Canada, Part 14. The Grasshoppers, Crickets, and Related Insects of Canada and Adjecent Regions. Research Branch Agriculture Canada Publication 1777:1-918.</p>
Data from: Oxygen limited thermal tolerance is seen in a plastron breathing insect, and can be induced in a bimodal gas exchanger
<p>Dataset on respiration and ctmax in two freshwater bugs, associated with the paper:<br> <strong>Verberk WCEP & Bilton DT (2015) </strong>Oxygen limited thermal tolerance is seen in a plastron breathing insect, and can be induced in a bimodal gas exchanger. <em>Journal of Experimental Biology </em>218: 2083-2088. doi: 10.1242/jeb.119560</p>
InsectSet47 & InsectSet66: Expanded datasets for automatic acoustic identification of insects (Orthoptera and Cicadidae)
<p><strong>Updated full version with training, validation and test sets.</strong></p> <p>Two newly compiled datasets for training neural networks to automatically identify insect species while comparing adaptive, waveform-based frontends to conventional mel-spectrogram frontends for audio feature extraction. This work was <a href="https://doi.org/10.1371/journal.pcbi.1011541">published in PLOS</a> Computational Biology and the machine learning implementations were published on <a href="https://github.com/mariusfaiss/InsectSet47-InsectSet66-Adaptive-Representations-of-Sound-for-Automatic-Insect-Recognition">Github</a>.</p> <p>These datasets expand on the previously published <a href="https://doi.org/10.5281/zenodo.7072196">InsectSet32</a> by including recently published collections of insect recordings by citizen scientists from around the world. Recordings from <a href="https://bio.acousti.ca/">BioAcoustica</a>, <a href="http://xeno-canto.org/">xeno-canto</a> and <a href="http://inaturalist.org/">iNaturalist</a>, as well as private collections by <a href="https://orcid.org/0000-0002-8929-2737">Baudewijn Odé</a> were downloaded and manually inspected. Files with strong noise interference or intense filtering, as well as files containing sounds of multiple species were removed to compile these datasets. The files were standardised to 44.1 kHz mono WAV files ranging in length from less than one second to several minutes. Files containing long periods without insect sounds were edited into multiple smaller files with silent periods no longer than 5 seconds. These files are marked as edits in the annotation file and should be assigned together into train/validation/test sets to prevent data leakage. The annotation files contain information for each recording, including the file name, species name and identifier, as well as the data subset they were included in for training the neural network (training, test, validation).</p> <p>InsectSet47 expands on <a href="https://doi.org/10.5281/zenodo.7072196">InsectSet32</a> with recordings from <a href="http://xeno-canto.org/">xeno-canto</a> and contains 1006 original recordings from 47 species, with at least ten files per species. The total length of InsectSet47 is 22 hours. InsectSet66 further expands on InsectSet47 by adding research-grade audio observations from <a href="http://inaturalist.org/">iNaturalist</a>, with a total of 1554 recordings from 66 species, a total length of over 24 hours and a minimum of ten files per species.</p> <p>The datasets were split into the training, validation and test sets while ensuring a roughly equal distribution of audio files and audio material for every species in all three subsets. This resulted in a 60/20/20 split (train/validation/test) by file number and a 64/19.5/16.5 split by file length.</p>
Aquatic Insect Adult Metals Dataset: Urban and Forested Watersheds in the Piedmont of NC - 2021-2022
This dataset reports concentrations of 6 target trace metals (copper, zinc, nickel, lead, chromium, and selenium) in unfiltered water, emergent aquatic adult insects (by family), biofilm mats (predominately algae), and tree roots submerged under stream water. Biological and water samples were collected from three streams in the Piedmont region of North Carolina, USA: a wastewater dominated site (Ellerbe Creek, near the USGS gage at Glen Road ), a stormwater dominated site (Ellerbe Creek, near the USGS gage on Club Blvd), and a stream draining a predominately forested watershed (New Hope Creek, near a StreamPULSE site at Hollow Rock Preserve). This data was submitted for publication in a manuscript that explores how metals are transported by aquatic emergent insects from stream ecosystems into terrestrial food webs.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.